supports both online and mini-batch mode

examples/encoder-decoder-coupling.lua

@@ -9,7 +9,7 @@ require 'rnn'
 
 torch.manualSeed(123)
 
-version = 1.1 --minibatch training
+version = 1.1 --supports both online and mini-batch training
 
 --[[ Forward coupling: Copy encoder cell and output to decoder LSTM ]]--
 function forwardConnect(encLSTM, decLSTM)
@@ -32,20 +32,20 @@ function main()
 
   -- Some example data
   local encInSeq, decInSeq, decOutSeq = torch.Tensor({{1,2,3},{3,2,1}}), torch.Tensor({{1,2,3,4},{4,3,2,1}}), torch.Tensor({{2,3,4,1},{1,2,4,3}})
-  decOutSeq = nn.SplitTable(2):forward(decOutSeq)
+  decOutSeq = nn.SplitTable(1, 1):forward(decOutSeq)
 
   -- Encoder
   local enc = nn.Sequential()
   enc:add(nn.LookupTable(opt.vocabSz, opt.hiddenSz))
-  enc:add(nn.SplitTable(2)) --Split along the second axis, where the first axis is the mini-batch
+  enc:add(nn.SplitTable(1, 2)) --works for both online and mini-batch mode
   local encLSTM = nn.LSTM(opt.hiddenSz, opt.hiddenSz)
   enc:add(nn.Sequencer(encLSTM))
   enc:add(nn.SelectTable(-1))
 
   -- Decoder
   local dec = nn.Sequential()
   dec:add(nn.LookupTable(opt.vocabSz, opt.hiddenSz))
-  dec:add(nn.SplitTable(2)) --Split along the second axis, where the first axis is the mini-batch
+  dec:add(nn.SplitTable(1, 2)) --works for both online and mini-batch mode
   local decLSTM = nn.LSTM(opt.hiddenSz, opt.hiddenSz)
   dec:add(nn.Sequencer(decLSTM))
   dec:add(nn.Sequencer(nn.Linear(opt.hiddenSz, opt.vocabSz)))